Informatics Tools for Pharmacogenomic Discovery using Practice-based Data

使用基于实践的数据进行药物基因组发现的信息学工具

• 批准号: 8629996
• 负责人: Joshua C. Denny
• 金额: $ 64.86万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-18 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8629996
• 关键词: Adverse event; Algorithms; Anthracyclines; Archives; Award; Biocompatible Materials; Biology; Biomedical Computing; Biomedical Research; Boston; Cardiotoxicity; Cells; Clinic; Clinical; Clinical Data; Clostridium difficile; Colitis; Communities; Computer software; Computerized Medical Record; Coupled; DNA; Data; Data Set; Databases; Disease; Drug Exposure; Drug toxicity; Electronics; Event; Foundations; Funding; Genetic Variation; Genomics; Genotype; Grant; Healthcare Systems; Heparin; Informatics; Information Management; Institution; Knowledge Discovery; Link; Medicine; Methods; Modeling; Morphologic artifacts; Natural Language Processing; Nature; Observational Study; Ontology; Outcome; Patients; Pediatric Hospitals; Pharmaceutical Preparations; Pharmacogenomics; Phenotype; Population Heterogeneity; Population Study; Research; Research Personnel; Resources; Sampling; Science; Site; Standardization; Structure; System; Terminology; Text; Thrombocytopenia; Time; TimeLine; Toxic effect; Treatment outcome; United States National Institutes of Health; Vancomycin; Vision; Warfarin; base; biobank; case control; clinical care; clopidogrel; data integration; disorder risk; drug efficacy; exome sequencing; genetic variant; improved; large-scale database; novel; open source; public health relevance; rapid growth; rare variant; response; success; surveillance study; tool; user-friendly; virtual

DESCRIPTION (provided by applicant): Rapid growth in the clinical implementation of large electronic medical records (EMRs) has led to an unprecedented expansion in the availability of dense longitudinal datasets for observational research. More recently, huge efforts have linked EMR databases with archived biological material, to accelerate research in personalized medicine. EMR- linked DNA biobanks have identified common and rare genetic variants that contribute to risk of disease. An appealing vision, which has not been extensively explored, is to use EMRs-linked biobanks for pharmacogenomic studies, which identify associations between genetic variation and drug efficacy and toxicity. The longitudinal nature of the data contained within EMRs make them ideal for quantifying drug outcome (both efficacy and toxicity). Efforts are already underway to link these EMRs across institutions, and standardize the definition of phenotypes for large-scale studies of treatment outcome, specifically within the context of routine clinical care. Despite its success, EMR-based pharmacogenomic studies are often hampered by its data-intensive nature -- it is time- consuming and costly to extract and integrate data from multiple heterogeneous EMR databases, for large-scale pharmacogenomic studies. The Informatics for Integrating Biology and the Bedside (i2b2) is a National Center for Biomedical Computing based at Partners Healthcare System. I2b2 has developed a scalable informatics framework to enable clinical researchers to repurpose existing EMR data for clinical and genomic discovery. In this study, we will collaborate with i2b2 to extend its informatics framework to the pharmacogenomics domain, by proposing the following specific aims: 1) Develop new methods to extract and model drug exposure and outcome information from EMR and integrate them with the i2b2 NLP components; 2) Build ontology tools to normalize and integrate pharmacogenomic data across different sites; 3) Conduct known and novel pharmacogenomic studies to evaluate and refine tools developed in Aim 1 and 2; and 4) Disseminate the developed informatics tools among pharmacogenomic researchers.

描述(由申请人提供)：大型电子病历(EMR)临床应用的快速增长导致用于观察性研究的密集纵向数据集的可获得性前所未有地扩大。最近，巨大的努力将电子病历数据库与存档的生物材料联系起来，以加快个性化医学的研究。与EMR相关的DNA生物库已经确定了导致疾病风险的常见和罕见的遗传变异。一个尚未被广泛探索的吸引人的愿景是使用eMRS连接的生物库进行药物基因组学研究，确定遗传变异与药物疗效和毒性之间的联系。EMR中包含的数据的纵向性质使其成为量化药物结果(疗效和毒性)的理想工具。已经在努力将这些机构的急诊医生联系起来，并将治疗结果大规模研究的表型定义标准化，特别是在常规临床护理的背景下。尽管取得了成功，但基于电子病历的药物基因组研究往往因其数据密集型的性质而受到阻碍--从多个不同的电子病历数据库中提取和整合数据用于大规模药物基因组研究既耗时又昂贵。整合生物学和床边的信息学(I2b2)是总部设在合作伙伴医疗系统的国家生物医学计算中心。I2b2开发了一个可扩展的信息学框架，使临床研究人员能够将现有的EMR数据重新用于临床和基因组发现。在这项研究中，我们将与i2b2合作，通过提出以下具体目标将其信息学框架扩展到药物基因组学领域：1)开发从EMR中提取药物暴露和结果信息并对其进行建模的新方法，并将它们与i2b2 NLP组件集成；2)构建本体工具，以标准化和集成不同站点的药物基因组数据；3)进行已知和新颖的药物基因组研究，以评估和改进目标1和2中开发的工具；以及4)在药物基因组研究人员中传播开发的信息学工具。